Green Sturgeon (Acipenser medirostris) are an anadromous threatened species of sturgeon found along the Pacific coast of North America. The southern Distinct Population Segment (sDPS) only spawns in the Sacramento River and is exposed to water temperatures kept artificially cold for the conservation and management of winter-run Chinook Salmon (Oncorhynchus tshawytscha). Past research has demonstrated costs of cold-water rearing including reduced growth rates, condition, and survivorship of juvenile Green Sturgeon. Our research investigates how the multiple stressors of water temperature and food limitation influence the metabolic performance and capacity of Green Sturgeon. We reared Green Sturgeon at two temperatures (13 and 19°C) and two ration amounts (100% and 40% of optimal feed). We then measured the routine (RMR) and maximum (MMR) metabolic rates of sturgeon acclimated to these rearing conditions across a range of acute temperature exposures (11 to 31°C). Among both temperature acclimation treatments, we found that feed restriction reduced RMR across a range of acute temperatures. The influence of feed restriction on RMR and MMR interacted with acclimation temperature. Fish reared at 13°C preserved their MMR and aerobic scope (AS: the difference between the MMR and RMR) despite feed restriction while fish fed reduced rations and acclimated to 19°C showed reduced MMR and AS capacity primarily at temperatures below 16°C. Our results indicate that the sympatry of threatened Green Sturgeon with endangered salmonids produces a conservation conflict. While cold-acclimated sturgeon preserved their metabolic scope despite feed restriction, warm-acclimated (19°C) fish exhibited reduced metabolic capacity at cold temperatures (< 16°C), indicating that cold water releases and poor food availability would constrain the metabolic performance of juvenile Green Sturgeon. Understanding the impacts of environmental conditions (e.g., temperature, dissolved oxygen) on the ecological interactions of Green Sturgeon will be necessary to determine how salmonid-focused management actions will influence this species.

The juvenile Green Sturgeon used in this experiment were spawned from wild nDPS adults caught on the Klamath River by fishermen of the Yurok Tribe in April 2016. Adult fish were transported to the Center for Aquatic Biology and Aquaculture (CABA) at UC Davis where they were spawned in accordance with methodology from Van Eenennaam et al. (2001). Eggs were held at 15°C until hatch, afterwards larvae were reared at 18°C in 815 L circular tanks. Larval fish were provided continuous flow of aerated, non-chlorinated fresh water from a dedicated well. After the development of exogenous feeding (ca. 15 days post hatch [dph], 0.1g, 3cm total length [L_T]; Van Eenennaam et al. 2001) fish were fed continuously ad libitum with semi-moist pellets (Ragen, Inc.; www.rangen.com) until the experiment began.

This experiment utilized at 2x2 design with fish experiencing one of two acclimation temperatures (13 or 19°C) and one of two feed rates (100% optimal feed rate [OFR] or 40% of optimal feed rate [LFR]). 32 dph fish were randomly placed into one of eight, 470 L round tanks initially set to 18°C (n= 25 per tank). Two replicate tanks were used for each temperature and feed ration combination. Water temperature was adjusted at a rate of 1°C day^-1 until acclimation temperatures were reached. Once target temperatures were achieved, ration treatments were initiated. Ration treatments were maintained until the end of the experiment (Table 1: Treatment Duration).

Feed rates for each treatment group were determined using the optimal feed rate model for A. transmontanus (Deng et al., 2003; Lee et al., 2014) as well as data on growth rates of A. medirostris under multiple feed rations (Zheng et al., 2015). These feed rations were the same as those used in Poletto et al. (2018) and further information regarding their derivation can be found there. To maintain 100% or 40% optimal feed the feed rates were recalculated every three weeks to reflect the increasing size of the fish and updated daily to account for fish mortality or experimental use. Feed restriction for both the 13 and 19°C groups began on the same day. Due to the effects of the ration on growth (see Poletto et al., 2018), treatment groups entered metabolic experiments at similar sizes, but different ages, and therefore different durations of exposure (Table 1). All groups were held under their treatment conditions for at least 33 days. All protocols and handling procedures were reviewed and approved by the UC Davis Institutional Animal Care and Use Committee (Protocol #18767).

Respirometry

Fish underwent metabolic trials in one of three, 5L automated swim tunnel respirometers (Loligo, DNK). Two tunnels were controlled using a single computer system and the third was controlled with a separate system. Water for each swim tunnel system was pumped (1260, Eheim, DEU) from a designated sump into an aerated water bath surrounding each swim tunnel which overflowed to the sump. Sump water was continually supplied with non-chlorinated fresh water from a designated well and aerated with porous air stones. The temperature of the sump (and therefore the swim tunnels) was maintained by circulating water through a heat pump (model DSHP-7; Aqua Logic Delta Star, USA) and pumping it back to the sump using a high-volume water pump (PM700, Pondmaster, USA). In addition, each sump contained an 800 W titanium heater (TH-800, Finnex, USA) connected to a thermostatic controller. Water temperature within the swim tunnels were maintained to a precision of ±0.5°C. Swim tunnels and associated sump systems were disinfected with bleach weekly to reduce potential for bacterial growth within the system.

Dissolved oxygen saturation within the swim tunnels was measured using fiber-optic dipping probes (Loligo, DNK) which continuously recorded via AutoResp™ software (version 2.3.0). Oxygen probes communicated to the AutoResp™ via a Witrox-4 oxygen meter (Loligo) for the two-tunnel system and a Witrox-1 oxygen meter for the single tunnel system. Oxygen probes were calibrated weekly using a two-point, temperature-paired calibration technique. Water velocity of the swim tunnels was quantified and calibrated using a flowmeter (Hontzcsh, DE) and regulated using a variable frequency drive controller (models 4x and 12K; SEW Eurodrive, USA). The velocity (precision <1 cm s^-1) for each tunnel was controlled remotely using the AutoResp™ program and a DAQ-M data acquisition device (Loligo). Swim tunnels were surrounded by shade cloth to reduce experimenter disturbance on the fish. Fish were remotely and individually monitored using infrared cameras (QSC1352W; Q-see, CHN) connected to a computer monitor and DVR recorder.

Oxygen consumption rates for both routine and maximum metabolic rates were measured via intermittent respirometry (Brett, 1964). A flush pump (DC30A-1230, Shenzhen Zhongke, China) for each tunnel pumped in aerated fresh water through the swim chamber and was automatically controlled via the AutoResp™ software and DAQ-M system. The DAQ-M would seal the tunnel and enable the measurement of oxygen consumption attributable to the fish. Oxygen saturation levels were kept above 80% and restored within 3 min with the influx of fresh, oxygenated water. Due to routine weekly sanitization, controls for background bacterial respiration were not conducted.

Routine Metabolic Rate (RMR)

Test fish were fasted for 23.8 ± 2.10 hours in 0.5m x 1.0m rectangular holding tanks with aerated flow-through water at their acclimation temperature. Fish were then transferred into a swim tunnel respirometer between 9:30 and 16:00 to account for differences in time needed to acclimate fish to test temperatures.  Fish were provided a 30-minute acclimation period at their acclimation temperature before a brief training swim wherein fish were exposed to a 25 cm/s current for 30 min followed by 10 min at 45 cm/s. After the training swim, fish were allowed to recover for 1 hr before adjusting the temperature of the swim tunnels. The temperature was adjusted at 2°C h^-1 to one of the swimming test temperatures (7 to 9 temperatures ranging from 11 to 31°C, Table 2). Once the temperature was achieved, fish were given another 1-hour acclimation period, after which RMR data was collected (Verhille et al., 2016; Zillig et al., 2023). Using intermittent flow respirometry oxygen data was sampled overnight (13.5 ± 2.63 hours). Fish activity was monitored by overhead infra-red cameras and data from fish which were not quiescent were discarded. RMR was calculated by averaging the three lowest RMR values (Poletto et al., 2017). RMR measurements were concluded by 08:14 ± 22 min.

Works Cited

Deng D-F, Koshio S, Yokoyama S, Bai SC, Shao Q, Cui Y, Hung SSO (2003) Effects of feeding rate on growth performance of white sturgeon (Acipenser transmontanus) larvae. Aquaculture 217: 589–598.

Lee S, Wang Y, Hung SSO, Strathe AB, Fangue NA, Fadel JG (2014) Development of optimum feeding rate model for white sturgeon (Acipenser transmontanus). Aquaculture 433: 411–420.

Poletto JB, Cocherell DE, Baird SE, Nguyen TX, Cabrera-Stagno V, Farrell AP, Fangue NA (2017) Unusual aerobic performance at high temperatures in juvenile Chinook salmon, Oncorhynchus tshawytscha. Conservation Physiology 5: 1–13.

Poletto JB, Martin B, Danner E, Baird SE, Cocherell DE, Hamda N, Cech Jr JJ, Fangue NA (2018) Assessment of multiple stressors on the growth of larval green sturgeon Acipenser medirostris: implications for recruitment of early life-history stages. Journal of Fish Biology 93: 952–960.

Van Eenennaam JP, Webb MAH, Deng X, Doroshov SI, Mayfield RB, Cech JJ, Hillemeier DC, Willson TE (2001) Artificial Spawning and Larval Rearing of Klamath River Green Sturgeon. Transactions of the American Fisheries Society 130: 159–165.

Verhille CE, English KK, Cocherell DE, Farrell AP, Fangue NA (2016) High thermal tolerance of a rainbow trout population near its southern range limit suggests local thermal adjustment. Conservation Physiology 4: 1–12.

Zillig KW, Lusardi RA, Cocherell DE, Fangue NA (2023) Interpopulation variation in thermal physiology among seasonal runs of Chinook salmon. Can J Fish Aquat Sci 00: 1–13.